Results 1 to 10 of about 1,477,861 (328)
Neural Activity in Quarks Language: Lattice Field Theory for a Network of Real Neurons. [PDF]
Entropy (Basel), 2023 Brain–computer interfaces have seen extraordinary surges in developments in recent years, and a significant discrepancy now exists between the abundance of available data and the limited headway made in achieving a unified theoretical framework.
Bardella G +7 more
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Wavelets and Lattice Field Theory.
EPJ Web of Conferences, 2018 When continuous fields are expanded in a wavelet basis, a D-dimensional continuum action becomes a (D+1)-dimensional lattice action on the naively discretized Poincare-patch coordinates of an Euclidean AdS(D+1).
Neuberger Herbert
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Real-time spin systems from lattice field theory [PDF]
Journal of High Energy Physics, 2023 We construct a lattice field theory method for computing the real-time dynamics of spin systems in a thermal bath. This is done by building on previous work of Takano with Schwinger-Keldysh and functional differentiation techniques. We derive a Schwinger-
Neill C. Warrington
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Variational structure of Luttinger-Ward formalism and bold diagrammatic expansion for Euclidean lattice field theory. [PDF]
Proc Natl Acad Sci U S A, 2018 Significance Many-body perturbation theory is one of the pillars of quantum many-body physics and has been used extensively to predict ground-state and excited-state electronic properties of real materials in the past few decades.
Lin L, Lindsey M.
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An alternative lattice field theory formulation inspired by lattice supersymmetry
Journal of High Energy Physics, 2017 We propose an unconventional formulation of lattice field theories which is quite general, although originally motivated by the quest of exact lattice supersymmetry. Two long standing problems have a solution in this context: 1) Each degree of freedom on
Alessandro D’Adda +2 more
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Diffusion models as stochastic quantization in lattice field theory [PDF]
Journal of High Energy Physics, 2023 In this work, we establish a direct connection between generative diffusion models (DMs) and stochastic quantization (SQ). The DM is realized by approximating the reversal of a stochastic process dictated by the Langevin equation, generating samples from
L. Wang, G. Aarts, K. Zhou
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A Gentle Introduction to Lattice Field Theory [PDF]
EntropyThe principles of Lattice Field Theory (LFT), in particular Lattice Gauge Theory (LGT), are explained for a nonspecialist audience. We describe some of the successes of the program; we also discuss the relationship between LFT and Quantum Cellular ...
Erhard Seiler
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Towards novel insights in lattice field theory with explainable machine learning [PDF]
Physical Review D, 2020 Machine learning has the potential to aid our understanding of phase structures in lattice quantum field theories through the statistical analysis of Monte Carlo samples. Available algorithms, in particular those based on deep learning, often demonstrate
Stefan Blücher +4 more
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RG-inspired machine learning for lattice field theory
EPJ Web of Conferences, 2018 Machine learning has been a fast growing field of research in several areas dealing with large datasets. We report recent attempts to use renormalization group (RG) ideas in the context of machine learning.
Foreman Sam +3 more
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Holographic mean field theory and Kondo lattice [PDF]
Journal of High Energy PhysicsWe first study a non-relativistic field theory model for the Kondo lattice by introducing the Kondo condensation, whose main effect is the hybridization of the flat band of the localized electron with dispersive one of the itinerant electron. The problem
Young-Kwon Han +3 more
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